Spatial and temporal-based diffusive correlation spectroscopy systems and methods

ABSTRACT

A system includes a photodetector array and a processor. The photodetector array includes a plurality of photodetectors and is configured to detect light that exits a body and output a plurality of electronic signals representative of the detected light as a function of time. The processor is configured to sample the electronic signals output by the photodetector array at a plurality of delay times during a predetermined time period to generate a sequence of frames, apply a plurality of temporal-based and spatial-based correlation measurement operations to sample values in each of the frames, generate, based on the application of the temporal-based and spatial-based correlation measurement operations to the sample values in each of the frames, a plurality of spatiotemporal correlation measure values for the light detected by the photodetector array, and include the plurality of spatiotemporal correlation measure values in a correlation map.

RELATED APPLICATIONS

The present application claims priority under 35 U.S.C. § 119(e) to U.S.Provisional Patent Application No. 62/687,657, filed on Jun. 20, 2018,and to U.S. Provisional Patent Application No. 62/717,664, filed on Aug.10, 2018. These applications are incorporated herein by reference intheir respective entireties.

BACKGROUND INFORMATION

Detection of brain activity is useful for medical diagnostics, imaging,neuroengineering, brain-computer interfacing, and a variety of otherdiagnostic and consumer-related applications. For example, cerebralblood flow ensures the delivery of oxygen and needed substrates totissue, as well as removal of metabolic waste products. Thus, detectionand quantification of cerebral blood flow is useful for diagnosis andmanagement of any brain injury or disease associated with ischemia orinadequate vascular autoregulation.

As another example, there is an increasing interest in measuringevent-related optical signals (also referred to as fast-opticalsignals). Such signals are caused by changes in optical scattering thatoccur when light propagating through active neural tissue (e.g., activebrain tissue) is perturbed through a variety of mechanisms, including,but not limited to, cell swelling, cell volume change, celldisplacement, changes in membrane potential, changes in membranegeometry, ion redistribution, birefringence changes, etc. Becauseevent-related optical signals are associated with neuronal activity,rather than hemodynamic responses, they may be used to detect brainactivity with relatively high temporal resolution,

Diffusive correlation spectroscopy (DCS), also referred to as diffusivewave spectroscopy (DWS), is a non-invasive optical procedure that hasbeen shown to be effective in measuring some types of brain activity,such as cerebral blood flow. A conventional DCS system directs highcoherence light (e.g., a laser) at a head of a subject. Some of thelight propagates through the scalp and skull and into the brain where itis scattered by moving red blood cells in tissue vasculature beforeexiting the head. This dynamic scattering from moving cells causes theintensity of the light that exits the head to temporally fluctuate. Todetect these temporal fluctuations, a conventional DCS system includes aphotodetector and a correlator. The photodetector detects individualphotons in the light that exits the head. The correlator keeps track ofthe arrival times of all photons detected by the photodetector andderives an intensity correlation function from temporal separationsbetween the photons. This intensity correlation function isrepresentative of the temporal fluctuations of the intensity of thelight that exits the head, and is therefore also indicative of bloodflow.

A conventional photodetector requires approximately one second toacquire enough signal for a meaningful measurement by a conventional DCSsystem. This is sufficient to detect changes in blood flow, which occurat relatively slow time scales (e.g., one second or more). However,conventional DCS systems do not operate fast enough to detectevent-related optical signals caused, for example, by cellular activity,which occurs at a much faster rate than changes in blood flow.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate various embodiments and are a partof the specification. The illustrated embodiments are merely examplesand do not limit the scope of the disclosure. Throughout the drawings,identical or similar reference numbers designate identical or similarelements.

FIG. 1 shows an exemplary configuration in which a DCS system isconfigured to determine spatiotemporal correlation measurement valuesaccording to principles described herein.

FIG. 2 illustrates an exemplary photodetector array according toprinciples described herein.

FIG. 3 shows a relationship between a photodetector array and a frameaccording to principles described herein.

FIG. 4 illustrates an exemplary heuristic that may be performed by aprocessor on a sequence of frames to generate a correlation mapaccording to principles described herein.

FIG. 5 shows pixel locations included in a pixel region of a frameaccording to principles described herein.

FIG. 6 illustrates an exemplary heuristic that may be performed by aprocessor on frames to generate a correlation map according toprinciples described herein.

FIG. 7 illustrates an alternative implementation of a DCS systemaccording to principles described herein.

FIG. 8 shows an exemplary DCS system that includes multiplephotodetector arrays according to principles described herein.

FIG. 9 shows an alternative configuration of the DCS system of FIG. 8according to principles described herein.

FIG. 10 illustrates an exemplary configuration in which an opticalcoupler is configured to split an optical beam output by a light sourceinto a sample and reference beam according to principles describedherein.

FIG. 11 is an exploded view of an exemplary non-invasive wearableassembly according to principles described herein.

FIG. 12 shows wearable assemblies positioned on an outer surface of abody according to principles described herein.

FIG. 13 illustrates an exemplary computing device according toprinciples described herein.

DETAILED DESCRIPTION

Spatial and temporal-based DCS systems and methods are described herein.In some examples, as will be described in more detail below, a lightsource (e.g., a laser diode) generates coherent light that enters a body(e.g., a head of a subject) at an input location. The incident lightscatters through many different optical paths within the body. Becauseof its high coherence, the light emerges from the body with the abilityto interfere with itself to produce an interference pattern at one ormore output locations. This interference pattern takes the form of afully developed speckle pattern at the one or more output locations. ADCS system as described herein may determine spatiotemporal correlationmeasurement values representative of speckle decorrelation (i.e., howspeckles within the speckle pattern vary with respect to time andspace).

To this end, the DCS system includes a K by L photodetector array and aprocessor coupled to an output of the photodetector array. Thephotodetector array includes a plurality of photodetectors eachconfigured to detect light that emerges from the body after it hasscattered within the body. Each photodetector is further configured tooutput an electronic signal representative of the detected light as afunction of time. Hence, the photodetector array as a whole isconfigured to output a plurality of electronic signals representative ofthe detected light as a function of time.

The processor is configured to sample the electronic signals output bythe photodetector array at a plurality of delay times during apredetermined time period to generate a sequence of frames eachcorresponding to a different delay time in the plurality of delay times.Each of the frames includes K times L digital sample values at K by Lpixel locations that correspond to locations of the photodetectorswithin the photodetector array.

The processor is further configured to apply a plurality oftemporal-based and spatial-based correlation measurement operations tothe sample values in each of the frames. Based on the application of thetemporal-based and spatial-based correlation measurement operations tothe sample values, the processor is configured to generate a pluralityof spatiotemporal correlation measure values for the light detected bythe photodetector array. These spatiotemporal correlation measure valuesrepresent speckle decorrelation associated with the light detected bythe photodetector array. The processor is further configured to includethe plurality of spatiotemporal correlation measure values in acorrelation map that corresponds to a predetermined delay time interval.The predetermined delay time interval represents a difference betweentwo delay times within the plurality of delay times.

By applying both temporal-based and spatial-based correlationmeasurement operations, as opposed to only temporal-based measurementoperations as applied in conventional DCS systems, the systems andmethods described herein provide additional useful information regardingthe decorrelation process of coherent light that exits the body afterscattering within the body. For example, the spatiotemporal correlationmeasure values generated by the systems and methods described herein mayprovide more accurate, useful, and distinguishing measures of brainactivity than correlation measures generated by conventional DCS systemsthat are only temporally based.

Moreover, by applying both temporal-based and spatial-based correlationmeasurement operations, the systems and methods described herein canrelax sampling requirements over time. For example, decorrelation ratesin the human head typically require sampling at 1 MHz when onlytemporal-based correlation measurement operations are performed.However, by also performing spatial-based correlation measurementoperations, the systems and methods described herein can obtain accuratemeasurements of decorrelation at sample rates that are much lower (e.g.,around 200 kHz).

Furthermore, by using a photodetector array that includes many (e.g.,100 to 100,000) photodetectors, as opposed to a single photodetector asused in conventional DCS systems, the systems and methods describedherein can dramatically speed up the sampling rate of DCS into thesub-millisecond range. By speeding up acquisition into this range, thesystems and methods described herein can sample at rates that aresufficient to resolve event-related optical signals (also referred to asfast-optical signals). Such signals are caused by changes in opticalscattering that occur when light propagating through active neuraltissue (e.g., active brain tissue) is perturbed through a variety ofmechanisms, including, but not limited to, cell swelling, cell volumechange, cell displacement, changes in membrane potential, changes inmembrane geometry, ion redistribution, birefringence changes, etc.Because event-related optical signals are associated with neuronalactivity, rather than hemodynamic responses, they may be used to detectbrain activity with relatively high temporal resolution. Resolution ofevent-related optical signals is described more fully in U.S.Provisional Application No. 62/692,074, filed Jun. 29, 2018, thecontents of which are hereby incorporated by reference in theirentirety.

These and other benefits and/or advantages that may be provided by thesystems and methods described herein will be made apparent by thefollowing detailed description.

FIG. 1 shows an exemplary configuration 100 in which a DCS system 102 isconfigured to determine spatiotemporal correlation measurement valuesrepresentative of speckle decorrelation. As shown, DCS system 102includes a photodetector array 104 composed of a plurality of individualphotodetectors (e.g., photodetector 106) and a processor 108 coupled toan output of photodetector array 104. Other components included inconfiguration 100 (e.g., a light source 110, a controller unit 112, andoptical fibers 114 and 116) are not shown to be included in DCS system102 in FIG. 1. However, one or more of these components may, in certainembodiments, be considered to be a part of DCS system 102.

Light source 110 may be implemented by any suitable component configuredto generate and emit high coherence light (e.g., light that has acoherence length of at least 5 centimeters) at a predetermined centerwavelength. For example, light source 110 may be implemented by ahigh-coherence laser diode.

Light source 110 is controlled by controller unit 112, which may beimplemented by any suitable computing device, integrated circuit, and/orcombination of hardware and/or software as may serve a particularimplementation. In some examples, controller unit 112 is configured tocontrol light source 110 by turning light source 110 on and off and/orsetting an intensity of light generated by light source 110. Controllerunit 112 may be manually operated by a user, or may be programmed tocontrol light source 110 automatically.

Light emitted by light source 110 travels via an optical fiber 114(e.g., a single-mode fiber or a multi-mode fiber) to a body 118 of asubject. In some implementations, body 118 is a head or any other bodypart of a human or other animal. Alternatively, body 118 may be anon-living object. For illustrative purposes, it will be assumed in theexamples provided herein that body 118 is a human head.

As indicated by arrow 120, the light emitted by light source 110 entersbody 118 at a first location 122 on body 118. To this end, a distal endof fiber 114 may be positioned at (e.g., right above or physicallyattached to) first location 122 (e.g., to a scalp of the subject). Insome examples, the light may emerge from fiber 114 and spread out to acertain spot size on body 118 to fall under a predetermined safetylimit.

After the light enters body 118, the light scatters through manydifferent optical paths within body 118. The light emerges from body 118at various locations. For example, as illustrated by arrow 124, thelight may exit from body 118 at location 126, which is different thanlocation 122. Because of its high coherence, the light may interferewith itself to produce an interference pattern in the form of a fullydeveloped speckle pattern at location 126.

As shown, a proximal end of optical fiber 116 (e.g., a multi-modeoptical fiber) is positioned at (e.g., right above or physicallyattached to) output location 126. In this manner, optical fiber 116 maycollect light as it exits body 124 at location 126 and carry the lightto photodetector array 104. The light may pass through one or morelenses and/or other optical elements (not shown) that direct the lightonto each of the photodetectors 106 included in photodetector array 104.

FIG. 2 illustrates photodetector array 104 in more detail. As shown,photodetector array includes a plurality of photodetectors 106 arrangedin a K by L array. In the example of FIG. 2, K and L are both equal tosix. However, it will be recognized that photodetector array 104 mayhave any other suitable dimension where K times L is greater than one.In some examples, photodetector array 104 includes between 10 and100,000 photodetectors.

Each photodetector 106 is labeled in FIG. 2 with indices that indicate aposition (i.e., a row number and a column number) of the photodetectorwithin photodetector array 104. For example, photodetector 106-1-1 islocated in the first row and first column of photodetector array 104 andphotodetector 106-6-6 is located in the sixth row and sixth column ofphotodetector array 104. As shown, each photodetector 106 may bedisposed on a surface 202. Surface 202 may be implemented by a printedcircuit board (PCB), an ASIC, or any other suitable surface. In someexamples, each photodetector 106 may be created via lithography on asilicon substrate, and then wire-bonded and packaged like other similarCMOS image chips.

Photodetectors 106 may each be implemented by any suitable circuitconfigured to detect individual photons of light incident uponphotodetectors 106. For example, each photodetector 106 may beimplemented by a single photon avalanche diode (SPAD) circuit. Unlikeconventional SPAD circuits, the SPAD circuits that implementphotodetectors 106 operate in a freely-running configuration, as opposedto a time-correlated single-photon-counting configuration.

Photodetectors 106 may each detect light that exits the body at location126 and output an electronic signal representative of the detected lightas a function of time. Because there are K times L photodetectors 106,photodetector array 104 outputs K times L electronic signals, where eachphotodetector 106 generates a different one of the K times L electronicsignals.

To illustrate, a photodetector (e.g., photodetector 106-1-1) may detectlight and output an electronic signal representative of the detectedlight as a function of time by detecting individual photons as theyarrive at the photodetector and outputting an analog pulse each time aphoton is detected. Hence, the electronic signal may include a series ofpulses, where each pulse represents an arrival time of a photon.Alternatively, the photodetector may track how many photons arrive atthe photodetector during a particular time interval (e.g., 10microseconds) and output a count value representative of this number. Inthis case, the electronic signal output by the photodetector may includea series of values each representative of a number of photons that hitthe photodetector during subsequent time intervals.

Photodetectors 106 may be configured to operate in a freely running modeas opposed to a time-correlated single photon counting mode. In otherwords, the photodetectors 106 used in connection with the systems andmethods described herein may simply output pulses when photons aredetected without having to determine actual arrival times of thephotons. This advantageously reduces the complexity and cost of thephotodetectors 106 compared to conventional DCS systems that usetime-of-flight optical measurement systems for in-vivo detection.

Processor 108 may be implemented by one or more physical processing(e.g., computing) devices. In some examples, processor 108 may executesoftware configured to perform one or more of the operations describedherein. Processor 108 is configured to sample the electronic signalsoutput by photodetector array 104 at N delay times during a time periodT to generate a sequence of N frames. The time period T may be of anysuitable duration (e.g., less than or equal to one microsecond). N mayalso have any suitable value greater than one. For example, N may bebetween 10 and 100,000.

FIG. 3 shows a relationship between photodetector array 104 and a frame302 included in the N frames generated by processor 108 sampling theelectronic signals output by photodetector array 104 at a particulardelay time. Each of the N frames generated by processor 108 has the samedimensions and structure as frame 302.

As shown, frame 302 has K by L pixel locations 304. Each pixel location304 is labeled in FIG. 3 with indices that indicate a position (i.e., arow number and a column number) of the pixel location 304 within frame302. For example, pixel location 304-1-1 is located in the first row andfirst column of frame 302 and pixel location 304-6-6 is located in thesixth row and sixth column of frame 302. Each pixel location 304corresponds to a location of a particular photodetector 106 inphotodetector array 104. For example, pixel location 304-1-1 correspondsto a location of photodetector 106-1-1 in photodetector array 104, pixellocation 304-1-2 corresponds to a location of photodetector 106-1-2 inphotodetector array 104, etc.

As mentioned, frame 302 is generated by processor 108 sampling theelectronic signals output by photodetector array 104 at a particulardelay time. This sampling is represented in FIG. 3 by arrow 306 and maybe performed in accordance with any suitable signal processingheuristic. The sampling generates a plurality of digital sample valuesthat are included in frame 302 at pixel locations 304. For example,frame 302 includes a digital sample value at pixel location 304-1-1 ofan electronic signal output by photodetector 106-1-1, a digital samplevalue at pixel location 304-1-2 of an electronic signal output byphotodetector 106-1-2, etc.

Processor 108 may apply a plurality of temporal-based and spatial-basedcorrelation measurement operations to the sample values in each of the Nframes generated by processor 108. Based on the application of thetemporal-based and spatial-based correlation measurement operations tothe sample values, processor 108 may generate a plurality ofspatiotemporal correlation measure values for the light detected byphotodetector array 104. Processor 108 may include the plurality ofspatiotemporal correlation measure values in one or more correlationmaps that each corresponding to a different predetermined delay timeinterval.

FIG. 4 illustrates an exemplary heuristic that may be performed byprocessor 108 on a sequence of frames 302 to generate a correlation map402 that corresponds to a delay time interval of one, where the delaytime interval is defined as an integer number of delay times betweenframes, from which frames will be considered to generate a particularcorrelation measurement. As shown, the sequence of frames 302 includesframes 302-1 through 302-N. Each frame 302 is generated by processor 108sampling the electronic signals output by photodetector array 104 at aparticular delay time. For example, frame 302-1 is generated byprocessor 108 sampling the electronic signals output by photodetectorarray 104 at a first delay time, frame 302-2 is generated by processor108 sampling the electronic signals output by photodetector array 104 ata second delay time immediately subsequent to the first delay time, etc.Each frame 302 is therefore temporally spaced from a subsequent frame302 by a delay time interval (dt) of one (i.e., dt=1). The same sequenceof frames 302 is shown three different times in FIG. 4 to illustrate howframes 302 are processed by processor 108, as will be made apparentbelow.

In the example of FIG. 4, processor 108 generates correlation map 402 byapplying a plurality of temporal-based and spatial-based correlationmeasurement operations to sample values included in a plurality ofoverlapping pixel regions (e.g., pixel regions 304-1 through 304-3). Theoverlapping pixel regions 304 are shaded and surrounded by a thickborder for illustrative purposes. In the particular example of FIG. 4,each pixel region 404 includes a three by three block of pixellocations. For example, pixel region 404-1 includes pixel locations inthe top-left corner of frame 302-1. With reference to FIG. 3, thesepixel locations include pixel locations 304-1-1, 304-1-2, 304-1-3,304-2-1, 304-2-2, 304-2-3, 304-3-1, 304-3-2, and 304-3-3. As shown,pixel region 404-2 overlaps with and is offset from pixel region 404-1by one pixel column to the right. Likewise, pixel region 404-3 overlapswith and is offset from pixel region 404-2 by one pixel column to theright. Other pixel regions of the same size (e.g., a pixel region thatoverlaps with and is offset from pixel region 404-1 by one row down) arenot specifically highlighted in FIG. 4. However, it will be recognizedthat in the example of FIG. 4, sixteen three by three pixel regions fitwithin each of frames 302.

It will be recognized that while three by three pixel regions are shownin FIG. 4, the pixel regions may alternatively be of any other suitablesize. In general, each pixel region may include Px by Py pixellocations, where Px times Py is greater than one.

Correlation map 402 includes a plurality of locations 406 (e.g.,locations 406-1 through 406-3) that each correspond to a particular oneof the overlapping pixel regions 404 (i.e., each location 406 includes aspatiotemporal correlation measure value corresponding to one of theoverlapping pixel regions 404). For example, in the example of FIG. 4,location 406-1 corresponds to pixel region 404-1, location 406-2corresponds to pixel region 404-2, and location 406-3 corresponds topixel region 404-3. Hence, the size of correlation map 402 depends onthe number of overlapping pixel regions 404 included in each frame 302.In the example of FIG. 4, because there are a total of sixteen possibleoverlapping pixel regions 404 in frames 302, correlation map 402 mayinclude sixteen locations 406, arranged in a four by four matrix.

Exemplary temporal-based and spatial-based correlation measurementoperations that may be performed by processor 108 with respect to pixelregion 404-1 will now be described. Because correlation map 402corresponds to a delay time interval of one, processor 108 may firstapply a plurality of temporal-based correlation measurement operationsto sample values included in corresponding pixel locations within pixelregion 404-1 for each subsequent and overlapping pair of frames 302(i.e., frames 302-1 and 302-2, frames 302-2 and 302-3, etc.).

To illustrate, FIG. 5 shows pixel locations 304-1-1 and 304-1-2 includedin pixel region 404-1 of each of frames 302-1 through 302-3. Only two ofthe nine pixel locations of pixel region 404-1 are shown in FIG. 5 forillustrative purposes. As shown, frames 302 each include a sample value502 at each of pixel locations 304-1-1 and 304-1-2. For example, frame302-1 includes a sample value 502-1 at pixel location 304-1-1 and asample value 502-2 at pixel location 304-1-2, frame 302-2 includes asample value 502-3 at pixel location 304-1-1 and a sample value 502-4 atpixel location 304-1-2, and frame 302-3 includes a sample value 502-5 atpixel location 304-1-1 and a sample value 502-6 at pixel location304-1-2.

As represented by arrow 504-1, processor 108 may apply a firsttemporal-based correlation measurement operation to frames 302-1 and302-2 by processing sample value 502-1 with sample value 502-3 to obtaina first temporal correlation measure value 506-1 for pixel location304-1-1. Likewise, as represented by arrow 504-2, processor 108 mayapply a second temporal-based correlation measurement operation toframes 302-1 and 302-2 by processing sample value 502-2 with samplevalue 502-4 to obtain a temporal correlation measure value 506-2 forpixel location 304-1-2.

Processor 108 may similarly apply temporal-based correlation measurementoperation to frames 302-2 and 302-3. For example, as represented byarrow 504-3, processor 108 may apply a first temporal-based correlationmeasurement operation to frames 302-2 and 302-3 by processing samplevalue 502-3 with sample value 502-5 to obtain a second temporalcorrelation measure value 506-3 for pixel location 304-1-1. Likewise, asrepresented by arrow 504-4, processor 108 may apply a secondtemporal-based correlation measurement operation to frames 302-2 and302-3 by processing sample value 502-4 with sample value 502-6 to obtaina second temporal correlation measure value 506-4 for pixel location304-1-2.

Processor 108 may similarly process sample values included in each ofthe other corresponding pixel locations included in pixel region 404-1of frames 302-1 and 302-2, frames 302-2 and 302-3, etc. until processor108 has obtained temporal correlation measurement values 506 for eachpixel location of pixel region 404-1 in each subsequent and overlappingpair of frames 302.

Processor 108 may process a first sample value (e.g., sample value502-1) with a second sample value (e.g., sample value 502-3) to obtain atemporal correlation measurement value (e.g., temporal correlationmeasurement value 506-1) in any suitable manner. For example, processor108 may multiply the first sample value with the second sample value.Processor 108 may also process N different sample values in a repeatedmanner to obtain a temporal correlation measurement value. For example,processor 108 may multiply the first sample value with the second samplevalue, then multiply the second sample value with the third samplevalue, etc., and finally multiply the N−1th sample value with the Nthsample value, and then take the average of all of the N−1 products toobtain a temporal correlation measurement value. Example values of N mayrange from 10 to 10,000. Additional or alternative temporal-basedcorrelation measurement operations may be performed on the first andsecond sample values, or on the N sample values, to obtain a temporalcorrelation measurement value as may serve a particular implementation.

With reference again to FIG. 4, processor 108 may include (e.g., store)the obtained temporal correlation measurement values 506 for each pixellocation of pixel region 404-1 in a datacube 408-1 (also referred to asdatacube d₁₁) corresponding to pixel region 404-1. As shown, datacube408-1 is a three-dimensional array of temporal correlation measurevalues, and has dimensions of Px by Py by N−1. Datacube 408-1 may beconceptualized as having N−1 two-dimensional (2D) data matrices eachhaving Px times Py temporal correlation measurement values 506. Each 2Ddata matrix in datacube 408-1 corresponds to a particular pairing offrames 302. For example, a first 2D data matrix in datacube 408-1includes temporal correlation measurement values 506 generated based onsample values included in frames 302-1 and 302-2, a second 2D datamatrix in datacube 408-1 includes temporal correlation measurementvalues 506 generated based on sample values included in frames 302-2 and302-3, etc.

Processor 108 may similarly obtain and include temporal correlationmeasurement values 506 in datacubes for every other pixel region thatfits within frames 302. For example, processor 108 may obtain temporalcorrelation measurement values 506 for pixel region 404-2, and includethese temporal correlation measurement values 506 in a datacube 408-2(also referred to as datacube d₁₂). Likewise, processor 108 may obtaintemporal correlation measurement values 506 for pixel region 404-3, andinclude these temporal correlation measurement values 506 in a datacube408-3 (also referred to as datacube d₁₃).

Processor 108 may apply spatial-based correlation measurement operationsto the temporal correlation measurement values 506 included in eachdatacube 408. For example, with respect to datacube 408-1, processor 108may apply the spatial-based correlation measurement operations byprocessing together all of the temporal correlation measurement valuesincluded in a particular 2D data matrix included in datacube 408-1.

To illustrate, reference is again made to FIG. 5. As illustrated byarrows 508-1 and 508-2, processor 108 may process temporal correlationmeasure value 506-1 with temporal correlation measure value 506-2 (andany other temporal correlation measure values obtained by processor 108for the pair of frames 302-1 and 302-2) to obtain a first spatialcorrelation measure value 510-1. Likewise, as illustrated by arrows508-3 and 508-4, processor 108 may process temporal correlation measurevalue 506-3 with temporal correlation measure value 506-4 (and any othertemporal correlation measure values obtained by processor 108 for thepair of frames 302-2 and 302-3) to obtain a second spatial correlationmeasure value 510-2. This process may be repeated for each 2D datamatrix included in datacube 408-1.

Processor 108 may process temporal correlation measure values 506 witheach other in any suitable manner to obtain a spatial correlationmeasure value 510. For example, processor 108 may compute a variance ofthe temporal correlation measure values 506.

Processor 108 may combine each of the spatial correlation measure valuesgenerated for a datacube 408 into a single spatiotemporal correlationmeasure value for the pixel region 404 associated with the datacube 408.For example, processor 108 may combine spatial correlation measure value510-1, spatial correlation measure value 510-2, and any other spatialcorrelation measure value obtained for pixel region 404-1 into a singlespatiotemporal correlation measure value for pixel region 404-1. Thiscombination may be performed in any suitable way. For example, processor108 may add spatial correlation measure value 510-1, spatial correlationmeasure value 510-2, and any other spatial correlation measure valueobtained for pixel region 404-1 together to obtain the singlespatiotemporal correlation measure value for pixel region 404-1.

In general, the transformation of temporal correlation measure values indatacube 408-1 to a single spatiotemporal correlation measure value maybe represented by C[d₁₁, dt=1], where the function C can include anysuitable processing operation. Likewise, the transformation of temporalcorrelation measure values in datacube 408-2 to a single spatiotemporalcorrelation measure value may be represented by C[d₁₂, dt=1], thetransformation of temporal correlation measure values in datacube 408-3to a single spatiotemporal correlation measure value may be representedby C[d₁₃, dt=1], etc. One exemplary function C is the sum of spatialvariances over time, as describe above and as represented in thefollowing equation: C(d)=var[d[x,y,1)]+var[d[x,y,2)]+ . . .+var[d[x,y,N−1)], where x and y refer the different pixel locationswithin a pixel region, and where the sum is over N different framesseparated by a particular delay time interval.

The single spatiotemporal correlation measure values derived fromdatacubes 408 may be included by processor 108 in correspondinglocations 406 in correlation map 402. For example, the singlespatiotemporal correlation measure value derived from datacube 408-1 maybe included in location 406-1, the single spatiotemporal correlationmeasure value derived from datacube 408-2 may be included in location406-2, the single spatiotemporal correlation measure value derived fromdatacube 408-3 may be included in location 406-3, etc. This may beperformed in any suitable manner.

The process described in FIG. 4 may be repeated for additional delaytime intervals to generate additional correlation maps eachcorresponding to a different delay time interval. For example, FIG. 6illustrates an exemplary heuristic that may be performed by processor108 on frames 302 to generate a correlation map 602 that corresponds toa delay time interval of two. In this heuristic, processor 108 may applytemporal-based correlation measurement operations to pairs of frames 302that are separated by a delay time interval of two (e.g., frames 302-1and 302-3, frames 302-2 and 302-4 (not shown), etc.).

Any number of correlation maps may be generated by processor 108. Forexample, processor 108 may generate correlation maps corresponding todelay time intervals of dt=1, dt=2, dt=3, . . . , dt=G, where G may beany suitable number (e.g., between 10 and 1000). Here, G is analogous tothe maximum temporal extent of a standard decorrelation curve in DCS.The correlation maps generated by processor 108 may be transmitted byprocessor 108 to any suitable computing device configured to process thedata included in the correlation maps (e.g., by using the correlationmaps to generate a volumetric reconstruction of brain activity). In someexamples, processor 108 may transmit the correlation maps to controllerunit 102, which may use the data included in correlation maps to controlvarious aspects of DCS system 102.

FIG. 7 illustrates an alternative implementation of DCS system 102. FIG.7 is similar to FIG. 1, except that in FIG. 7, DCS system 102 includes apolarization device 702 and a cross polarizer 704. Polarization device702 is positioned in an optical path between an output of light source110 and body 118, and is configured to set a polarization of the lightgenerated by light source 110 to a predetermined state. Cross polarizer704 is configured to prevent light having the predetermined state frombeing applied to photodetector array 104. The use of polarization device702 and cross polarizer 704 may improve the ability to separate signalthat arises from the brain as opposed to the scalp and/or skull. This isbecause light that reflects off the scalp and/or skull likely still hasthe same polarization state that it had when it was output by lightsource 110. In contrast, much of the light that enters and emerges fromthe brain has had its polarization state randomly changed. Hence, byblocking light that has a polarization state that has not changed sincebeing generated by light source 110 from being detected by photodetectorarray 104, the systems and methods described herein may ensure that thelight that is detected by photodetector array 104 has actually enteredthe brain.

FIG. 8 shows an exemplary DCS system 800 that includes multiplephotodetector arrays 802 (e.g., photodetector array 802-1 andphotodetector array 802-1) configured to detect light that exits body118 at different locations. To facilitate operation of multiplephotodetector arrays 802, DCS system 800 includes a controller unit 804(which may be similar to controller unit 112), a light source assembly806, and a processor 808 (which may be similar to processor 108).

Light source assembly 806 is configured to generate a first optical beam810-1 that enters body 118 at a first entry location 812-1 and a secondoptical beam 810-2 that enters body 118 at a second entry location812-2. In the example of FIG. 8, light source assembly 806 isimplemented by a light source 814 (which may be similar to light source110), an optical coupler 816, and first and second optical modulators818-1 and 818-2. Light source 814 is configured to generate a singleoptical beam. Optical coupler 816 is connected to an output of lightsource 814 and configured to split the single optical beam into firstoptical beam 810-1 and second optical beam 810-2.

Optical modulator 818-1 is optically connected to optical coupler 816and configured to receive optical beam 810-1 and selectively allowoptical beam 810-1 to enter body 118 at the first entry location 812-1.Likewise, optical modulator 818-2 is optically connected to opticalcoupler 816 and configured to receive optical beam 810-2 and selectivelyallow optical beam 810-2 to enter body 118 at the second entry location812-2.

As shown, controller unit 804 may be communicatively coupled to opticalmodulators 818. Controller unit 804 may transmit instructions to opticalmodulators 818 to cause optical modulators 818 to selectively change theamplitude, phase, and/or polarization state of optical beams 810. Insome examples, controller unit 804 may transmit instructions to opticalmodulator 818-1 that cause optical modulator 818-1 to prevent opticalbeam 810-1 from entering the body 118 while optical beam 812-2 isentering the body 118. Likewise, controller unit 804 may transmitinstructions to optical modulator 818-2 that cause optical modulator818-2 to prevent optical beam 810-2 from entering the body 118 whileoptical beam 812-1 is entering the body 118. In this manner, DCS system800 may ensure that optical beams 810-1 and 810-2 do not interfere onewith another.

Photodetector array 802-1 is configured to detect light 820 (e.g., lightfrom either optical beam 810) that exits body 118 at a first exitlocation 824-1 and output electronic signals representative of the lightdetected by photodetector array 802-1 as a function of time. Likewise,photodetector array 802-2 is configured to detect light 820 (e.g., lightfrom either optical beam 810) that exits body 118 at a second exitlocation 824-2 and output electronic signals representative of the lightdetected by photodetector array 802-2 as a function of time.

Processor 808 is connected to outputs of photodetector arrays 802 and isconfigured to generate a first correlation map that includes a pluralityof spatiotemporal correlation measure values corresponding to the lightdetected by photodetector array 802-1 and a second correlation map thatincludes a plurality of spatiotemporal correlation measure valuescorresponding to the light detected by photodetector array 802-2. Thismay be performed in any of the ways described herein. The first andsecond correlation maps (and any other correlation map generated byprocessor 808 for either photodetector array 802) may be output to acomputing device (not shown), which may process the correlation maps inany suitable manner. Likewise, this extension to two photodetectorarrays 802 is generalizable to three or more photodetector arraysdistributed across the body.

FIG. 9 shows an alternative configuration 900 of DCS system 800. Inconfiguration 900, light source assembly 806 is implemented by multiplelight sources 901-1 and 902-2. Light source 902-1 is configured tooutput optical beam 810-1 and light source 902-2 is configured to outputoptical beam 810-2. In this configuration, each light source 902 may becontrolled by controller unit 804 to output optical beams havingdifferent wavelengths and/or other characteristics.

For example, optical beams 810-1 and 810-2 may have differentwavelengths. Photodetector arrays 802 may detect this light in series orin parallel and then perform a suitable post-processing step to obtainmore information about the decorrelation signal than would be possiblefrom measuring a single wavelength. For example, light sources 902-1 and902-2 may be turned on one at a time in series and photodetector arrays802 together with processor 808 may detect the light, digitize theresulting electronic signals, and generate correlation maps for eachwavelength. A separate computing device (not shown) may determine amulti-wavelength weighted combination, which may be used to help betterisolate decorrelation signal that arises from only scattering changes,as opposed to scattering and absorption and blood flow changes. Thisextension to two light sources 902 is generalizable to three or morelight sources distributed across the body.

FIG. 10 illustrates an exemplary configuration in which an opticalcoupler 1002 is configured to split an optical beam output by lightsource 110 such that a first optical beam 1004 (i.e., a sample beam)enters body 110 and a second optical beam 1006 (i.e., a reference beam)is applied directly to photodetector array 104. Optical beam 1006 may bereferred to as a flat reference beam and may be configured to boost asignal level of the light 118 that exits the body 110 above the noisefloor so that photodetector array 104 may more easily detect light 118.

In some examples, any of the photodetector arrays describe herein may beincluded as part of a wearable assembly configured to be positioned on abody of a user. For example, the wearable assembly may be worn on thehead of a user.

To illustrate, FIG. 11 is an exploded view of an exemplary non-invasivewearable assembly 1100. As shown, wearable assembly 1100 includes aphotodetector array 1102 that has a plurality of photodetectors (e.g.,photodetector 1104), an optical spacer 1106, and a pinhole array 1108that has a plurality of pinholes (e.g., pinhole 1110).

Optical spacer 1106 may be implemented by a sheet of glass or otherflexible transparent material of finite thickness and may be attached toa front surface 1112 of photodetector array 1102.

Pinhole array 1108 may be made out of any suitable material and may beattached to a front surface 1114 of optical spacer 1106. The pinholes ofpinhole array 1108 may be configured to be aligned with thephotodetectors of photodetector array 1102. Hence, if photodetectorarray 1102 is a K by L array that includes K times L photodetectors,pinhole array 1108 is also a K by L array that includes K times Lpinholes.

The pinholes of pinhole array 1108 are configured to be in physicalcontact with the body and allow only a certain amount of light to beincident upon each of the photodetectors in photodetector array 1102. Inother words, pinhole array 1108 blocks a certain amount of the specklepattern from being detected by each of the photodetectors inphotodetector array 1102. By blocking light, pinhole array 1108 mayreduce the number of speckles that fall upon each photodetector, whichmay improve the contrast of spatiotemporal correlation.

FIG. 12 shows three wearable assemblies 1100 positioned on an outersurface 1202 of body 110. As shown, in this configuration, there is noneed for optical fibers to be included to direct light exiting body 110to photodetector arrays 1102.

In some examples, a non-transitory computer-readable medium storingcomputer-readable instructions may be provided in accordance with theprinciples described herein. The instructions, when executed by aprocessor of a computing device, may direct the processor and/orcomputing device to perform one or more operations, including one ormore of the operations described herein. Such instructions may be storedand/or transmitted using any of a variety of known computer-readablemedia.

A non-transitory computer-readable medium as referred to herein mayinclude any non-transitory storage medium that participates in providingdata (e.g., instructions) that may be read and/or executed by acomputing device (e.g., by a processor of a computing device). Forexample, a non-transitory computer-readable medium may include, but isnot limited to, any combination of non-volatile storage media and/orvolatile storage media. Exemplary non-volatile storage media include,but are not limited to, read-only memory, flash memory, a solid-statedrive, a magnetic storage device (e.g. a hard disk, a floppy disk,magnetic tape, etc.), ferroelectric random-access memory (“RAM”), and anoptical disc (e.g., a compact disc, a digital video disc, a Blu-raydisc, etc.). Exemplary volatile storage media include, but are notlimited to, RAM (e.g., dynamic RAM).

FIG. 13 illustrates an exemplary computing device 1300 that may bespecifically configured to perform one or more of the processesdescribed herein. As shown in FIG. 13, computing device 1300 may includea communication interface 1302, a processor 1304, a storage device 1306,and an input/output (“I/O”) module 1308 communicatively connected one toanother via a communication infrastructure 1310. While an exemplarycomputing device 1300 is shown in FIG. 13, the components illustrated inFIG. 13 are not intended to be limiting. Additional or alternativecomponents may be used in other embodiments. Components of computingdevice 1300 shown in FIG. 13 will now be described in additional detail.

Communication interface 1302 may be configured to communicate with oneor more computing devices. Examples of communication interface 1302include, without limitation, a wired network interface (such as anetwork interface card), a wireless network interface (such as awireless network interface card), a modem, an audio/video connection,and any other suitable interface.

Processor 1304 generally represents any type or form of processing unitcapable of processing data and/or interpreting, executing, and/ordirecting execution of one or more of the instructions, processes,and/or operations described herein. Processor 1304 may performoperations by executing computer-executable instructions 1312 (e.g., anapplication, software, code, and/or other executable data instance)stored in storage device 1306.

Storage device 1306 may include one or more data storage media, devices,or configurations and may employ any type, form, and combination of datastorage media and/or device. For example, storage device 1306 mayinclude, but is not limited to, any combination of the non-volatilemedia and/or volatile media described herein. Electronic data, includingdata described herein, may be temporarily and/or permanently stored instorage device 1306. For example, data representative ofcomputer-executable instructions 1312 configured to direct processor1304 to perform any of the operations described herein may be storedwithin storage device 1306. In some examples, data may be arranged inone or more databases residing within storage device 1306.

I/O module 1308 may include one or more I/O modules configured toreceive user input and provide user output. I/O module 1308 may includeany hardware, firmware, software, or combination thereof supportive ofinput and output capabilities. For example, I/O module 1308 may includehardware and/or software for capturing user input, including, but notlimited to, a keyboard or keypad, a touchscreen component (e.g.,touchscreen display), a receiver (e.g., an RF or infrared receiver),motion sensors, and/or one or more input buttons.

I/O module 1308 may include one or more devices for presenting output toa user, including, but not limited to, a graphics engine, a display(e.g., a display screen), one or more output drivers (e.g., displaydrivers), one or more audio speakers, and one or more audio drivers. Incertain embodiments, I/O module 1308 is configured to provide graphicaldata to a display for presentation to a user. The graphical data may berepresentative of one or more graphical user interfaces and/or any othergraphical content as may serve a particular implementation.

In some examples, any of the systems, computing devices, processors,controller units, and/or other components described herein may beimplemented by computing device 1300. For example, processor 108,processor 108, controller unit 112, and/or controller unit 804 may beimplemented by processor 1304.

In the preceding description, various exemplary embodiments have beendescribed with reference to the accompanying drawings. It will, however,be evident that various modifications and changes may be made thereto,and additional embodiments may be implemented, without departing fromthe scope of the invention as set forth in the claims that follow. Forexample, certain features of one embodiment described herein may becombined with or substituted for features of another embodimentdescribed herein. The description and drawings are accordingly to beregarded in an illustrative rather than a restrictive sense.

What is claimed is:
 1. A system comprising: a wearable assemblyconfigured to be positioned on a body and comprising: a K by Lphotodetector array comprising a plurality of photodetectors andconfigured to detect light that exits the body at a second locationafter the light enters the body at a first location different than thesecond location and scatters within the body, and output a plurality ofelectronic signals representative of the detected light as a function oftime, where each photodetector included in the photodetector array isconfigured to output a different one of the electronic signals; anoptical spacer attached to a front surface of the photodetector array; apinhole array attached to a front surface of the optical spacer, thepinhole array having a K by L array of pinholes configured to be alignedwith the photodetectors, the pinhole array configured to be in physicalcontact with the body and allow a certain amount of light to be incidentupon each of the photodetectors; and a processor coupled to an output ofthe photodetector array and configured to sample the electronic signalsoutput by the photodetector array at a plurality of delay times during apredetermined time period to generate a sequence of frames eachcorresponding to a different delay time in the plurality of delay times,where each of the frames includes K times L digital sample values at Kby L pixel locations that correspond to locations of the photodetectorswithin the photodetector array, apply a plurality of temporal-based andspatial-based correlation measurement operations to the sample values ineach of the frames, generate, based on the application of thetemporal-based and spatial-based correlation measurement operations tothe sample values in each of the frames, a plurality of spatiotemporalcorrelation measure values for the light detected by the photodetectorarray, and include the plurality of spatiotemporal correlation measurevalues in a correlation map that corresponds to a predetermined delaytime interval that represents a difference between two delay timeswithin the plurality of delay times.
 2. The system of claim 1, whereinthe processor is configured to apply the plurality of temporal-based andspatial-based correlation measurement operations to the sample values ineach of the frames by applying the plurality of temporal-based andspatial-based correlation measurement operations to sample valuesincluded in a plurality of overlapping pixel regions in each of theframes, where each of the pixel regions includes Px by Py pixellocations, and Px times Py is greater than one; and the plurality ofspatiotemporal correlation measure values each correspond to a differentone of the overlapping pixel regions.
 3. The system of claim 2, wherein:the predetermined delay time interval is one; a first pixel region inthe overlapping pixel regions includes a first pixel location and asecond pixel location; each of the frames includes a first sample valuecorresponding to the first pixel location and a second sample valuecorresponding to the second pixel location; the frames include a firstframe corresponding to a first delay time, a second frame correspondingto a second delay time immediately subsequent to the first delay time,and a third frame corresponding to a third delay time immediatelysubsequent to the second delay time; and the processor is configured toapply the temporal-based correlation measurement operations byprocessing the first sample value in the first frame with the firstsample value in the second frame to obtain a first temporal correlationmeasure value for the first pixel location, processing the first samplevalue in the second frame with the first sample value in the third frameto obtain a second temporal correlation measure value for the firstpixel location, processing the second sample value in the first framewith the second sample value in the second frame to obtain a firsttemporal correlation measure value for the second pixel location, andprocessing the second sample value in the second frame with the secondsample value in the third frame to obtain a second temporal correlationmeasure value for the second pixel location.
 4. The system of claim 3,wherein the processing of the first sample value in the first frame withthe first sample value in the second frame to obtain the first temporalcorrelation measure value for the first pixel location comprisesmultiplying the first sample value in the first frame with the firstsample value in the second frame.
 5. The system of claim 3, wherein theprocessor is configured to apply the spatial-based correlationmeasurement operations by: processing the first temporal correlationmeasure value for the first pixel location with the first temporalcorrelation measure value for the second pixel location to obtain afirst spatial correlation measure; and processing the second temporalcorrelation measure value for the first pixel location with the secondtemporal correlation measure value for the second pixel location toobtain a second spatial correlation measure.
 6. The system of claim 5,wherein the processing of the first temporal correlation measure valuefor the first pixel location with the first temporal correlation measurevalue for the second pixel location comprises computing a variance ofthe first temporal correlation measure value for the first pixellocation and the first temporal correlation measure value for the secondpixel location.
 7. The system of claim 6, wherein the processor isconfigured to: combine the first and second spatial correlation measurevalues to obtain a single spatiotemporal correlation measure value forthe first pixel region; and include the single spatiotemporalcorrelation measure value in the correlation map at a location thatcorresponds to the first pixel region.
 8. The system of claim 7, whereinthe combining of the first and second spatial correlation measure valuescomprises adding the first and second spatial correlation measurevalues.
 9. The system of claim 7, wherein: a second pixel region in theoverlapping pixel regions includes the second pixel location and a thirdpixel location; each of the frames further includes a third sample valuecorresponding to the third pixel location; and the processor is furtherconfigured to apply the temporal-based correlation measurementoperations by processing the third sample value in the first frame withthe third sample value in the second frame to obtain a first temporalcorrelation measure value for the third pixel location, and processingthe third sample value in the second frame with the third sample valuein the third frame to obtain a second temporal correlation measure valuefor the third pixel location.
 10. The system of claim 9, wherein theprocessor is further configured to apply the spatial-based correlationmeasurement operations by: processing the first temporal correlationmeasure value for the second pixel location with the first temporalcorrelation measure value for the third pixel location to obtain a thirdspatial correlation measure; and processing the second temporalcorrelation measure value for the second pixel location with the secondtemporal correlation measure value for the third pixel location toobtain a fourth spatial correlation measure.
 11. The system of claim 10,wherein the processor is further configured to: combine the third andfourth spatial correlation measure values to obtain a singlespatiotemporal correlation measure value for the second pixel region;and include the single spatiotemporal correlation measure value for thesecond pixel region in the correlation map at a location thatcorresponds to the second pixel region.
 12. The system of claim 3,wherein the frames further include a fourth frame corresponding to afourth delay time immediately subsequent to the third delay time and afifth delay time immediately subsequent to the fourth delay time, andwherein the processor is further configured to: generate, based on theapplication of the temporal-based and spatial-based correlationmeasurement operations to the sample values in each of the frames, anadditional plurality of spatiotemporal correlation measure values forthe light detected by the photodetector array; and include theadditional plurality of spatiotemporal correlation measure values in anadditional correlation map that corresponds to a predetermined delaytime interval equal to two.
 13. The system of claim 12, wherein theprocessor is configured to apply the temporal-based correlationmeasurement operations to generate the additional correlation map by:processing the first sample value in the first frame with the firstsample value in the third frame to obtain a first temporal correlationmeasure value associated with the additional correlation map for thefirst pixel location; processing the first sample value in the thirdframe with the first sample value in the fifth frame to obtain a secondtemporal correlation measure value associated with the additionalcorrelation map for the first pixel location; processing the secondsample value in the first frame with the second sample value in thethird frame to obtain a first temporal correlation measure valueassociated with the additional correlation map for the second pixellocation; and processing the second sample value in the third frame withthe second sample value in the fifth frame to obtain a second temporalcorrelation measure value associated with the additional correlation mapfor the second pixel location.
 14. The system of claim 13, wherein theprocessor is configured to apply the spatial-based correlationmeasurement operations to generate the additional correlation map by:processing the first temporal correlation measure value associated withthe additional correlation map for the first pixel location with thefirst temporal correlation measure value associated with the additionalcorrelation map for the second pixel location to obtain a first spatialcorrelation measure associated with the additional correlation map; andprocessing the second temporal correlation measure value associated withthe additional correlation map for the first pixel location with thesecond temporal correlation measure value associated with the additionalcorrelation map for the second pixel location to obtain a second spatialcorrelation measure associated with the additional correlation map. 15.The system of claim 14, wherein the processor is further configured to:combine the first and second spatial correlation measure valuesassociated with the additional correlation map to obtain a singlespatiotemporal correlation measure value associated with the additionalcorrelation map for the first pixel region; and include the singlespatiotemporal correlation measure value associated with the additionalcorrelation map in the additional correlation map at a location thatcorresponds to the first pixel region.
 16. The system of claim 1,wherein the light that enters the body has a coherence length of atleast 5 centimeters.
 17. The system of claim 1, further comprising alight source configured to generate the light that enters the body. 18.The system of claim 17, wherein the light source is a high-coherencelaser diode.
 19. The system of claim 17, further comprising apolarization device positioned in an optical path between an output ofthe light source and the body, the polarization device configured to seta polarization of the light generated by the light source to apredetermined state.
 20. The system of claim 19, further comprising across polarizer positioned between an optical path from the body to thephotodetector array, the cross polarizer configured to prevent lighthaving a polarization of the predetermined state from being applied tothe photodetector array.
 21. The system of claim 17, further comprisinga single-mode optical fiber configured to be connected to an output ofthe light source and to the body at the first location, wherein thelight generated by the light source travels to the body by way of thesingle-mode optical fiber.
 22. The system of claim 17, furthercomprising a controller unit configured to control the light source by:turning on and off the light source; and setting an intensity of thelight generated by the light source.
 23. The system of claim 17, furthercomprising an optical coupler connected to an output of the lightsource, the optical coupler configured to split the light into a firstoptical beam that enters the body at the first location and a secondoptical beam that is applied directly to the photodetector array, thesecond optical beam configured to boost a signal level of the light thatexits the body at the second location.
 24. The system of claim 1,further comprising a multi-mode optical fiber configured to be connectedto the body at the second location and to an input of the photodetectorarray, wherein the light that exits the body at the second locationtravels to the photodetector array by way of the multi-mode opticalfiber.
 25. The system of claim 1, wherein the photodetectors are singlephoton avalanche diode (SPAD) circuits.
 26. The system of claim 1,wherein the predetermined time period is less than or equal to onemicrosecond.
 27. The system of claim 1, wherein the sequence of framescomprises between 10 frames and 100,000 frames.
 28. The system of claim1, wherein the body is a head of a patient.